224 citations · 3.2k across the 170 of their papers we have counts for
5 papers · 1 filter
CoSCL: Cooperation of Small Continual Learners is Stronger than a Big One
Liyuan Wang, Xingxing Zhang, Qian Li +2
Continual learning requires incremental compatibility with a sequence of tasks. However, the design of model architecture remains an open question: In general, learning all tasks w…
Thompson Sampling for (Combinatorial) Pure Exploration
Siwei Wang, Jun Zhu
Existing methods of combinatorial pure exploration mainly focus on the UCB approach. To make the algorithm efficient, they usually use the sum of upper confidence bounds within arm…
NeuralEF: Deconstructing Kernels by Deep Neural Networks
Zhijie Deng, Jiaxin Shi, Jun Zhu
Learning the principal eigenfunctions of an integral operator defined by a kernel and a data distribution is at the core of many machine learning problems. Traditional nonparametri…
Deep Ensemble as a Gaussian Process Approximate Posterior
Zhijie Deng, Feng Zhou, Jianfei Chen +2
Deep Ensemble (DE) is an effective alternative to Bayesian neural networks for uncertainty quantification in deep learning. The uncertainty of DE is usually conveyed by the functio…
Query-Efficient Black-box Adversarial Attacks Guided by a Transfer-based Prior
Yinpeng Dong, Shuyu Cheng, Tianyu Pang +2
Adversarial attacks have been extensively studied in recent years since they can identify the vulnerability of deep learning models before deployed. In this paper, we consider the…